1. Field of the Invention
This invention relates to an apparatus including block floating processing for a compressing a digital signal. The invention relates more particularly to an apparatus for compressing a digital signal, in which spectral components in the frequency domain derived from the digital input signal in the time domain are divided into blocks corresponding to so. called critical bands, and block floating processing is applied to each block.
2. Prior art
Among the techniques known for compressing a digital audio signal, block floating divides digital data into blocks of a predetermined number of samples and block floating processing is applied to each block. When block floating is applied to a block, the maximum absolute value of the samples in the block is found, and the maximum absolute value is used as a common block floating coefficient or scale factor for all the samples in the block.
Also, orthogonal transform coding is known in which a signal in the time domain is transformed into spectral components in the frequency domain. The spectral components are then quantized. As examples of orthogonal transform coding, it is known to apply Fast Fourier Transform (FFT) or Discrete Cosine Transform DCT) processing to a PCM audio signal divided in the time domain into blocks of a fixed number of samples.
An apparatus for compressing a digital signal has been proposed in which the above-mentioned technologies are combined to divide spectral components in the frequency domain into blocks corresponding to predetermined frequency bands, e.g., to so-called critical bands, and to apply block floating processing to the spectral components in each block.
FIG. 11 shows the configuration of part of an apparatus for compressing a digital signal which incorporates both orthogonal transform processing and block floating processing.
In FIG. 11, a digital input signal such as a PCM audio signal, etc. delivered to the input terminal 41 is temporarily stored in the buffer memory 42. The signal is then orthogonally transformed, e.g., by the orthogonal transform circuit 43, which is, e.g. a FFT (Fast Fourier Transform) circuit. FIG. 11 shows the circuit section for the (k-1)-th and k-th critical bands, in both of which, the number of spectral components (FFT coefficients) is, e.g., eight. The block of eight spectral components of the (k-1)-th band is sent to the peak detector 44 and the quantizer 45. The spectral components are quantized using a scale factor corresponding to the peak value detected by the peak detector 44. The block of eight spectral components of the k-th band is also sent to the peak detector 46 and the quantizer 47. An example of the block of eight spectral components of the k-th band is shown in FIG. 12.
The quantizers 45 and 47 quantize the spectral components in each respective band using a scale factor for the band derived from the peak value provided by the respective peak detectors 44 and 46, and the allocated bit numbers n.sub.k-1, n.sub.k for the respective bands, determined by other processing. The resulting quantized spectral components are sent to the multiplexer 48, where they are combined with the spectral components of other bands and with auxiliary information, such as the allocated bit number, etc. The multiplexed signal is fed to the output terminal 49.
When the spectral components in a critical band differ significantly from one another, e.g., when the part of the input signal represented by the spectral coefficients in the critical band is highly tonal, as shown in FIG. 12, for example, there could be, within the block B(k), a portion B(k, b) in which the spectral components corresponding to the highly-tonal signal are dominant, and a portion B(k, a) in which no spectral component is dominant. In this case, if block floating processing is carried out using the peak value P in the block B(k) as the scale factor, the portion B(k, b) in which spectral components corresponding to the highly tonal signal are dominant is no problem, but degradation occurs with respect to the portion B(k, a) in which no spectral component is dominant.
FIG. 12 shows an example in which the allocated bit number n.sub.k is 3. It can be seen that when quantizing takes place using a quantizing step size of .DELTA., the quantizing step size .DELTA. is relatively large compared with the spectral components in the portion B(k, a) in which no spectral component is dominant. If quantizing is carried out using a quantizing step that is relatively large compared with the signal, the quantizing noise is large, resulting in the disadvantage that quantizing noise might be heard when the compressed signal is expanded and reproduced.